Writing maintainable code is important for reducing the time, expense, and risk of maintaining software. Junior developers are most concerned about getting things functional and leaving it at that. However, enterprise projects quickly become complex. And when software is unmaintainable, adding a feature or fixing a bug that would take five minutes could take five hours. That’s because disorganized code requires a great deal of scrutiny and analysis to ensure the developer is not introducing new bugs. And that significantly increases development time, introduces risks, and increases costs. Creating a well-organized project from the start prevents all of that and makes the project quick and easy to debug, extend, and maintain.
Keep it Simple
Try to keep the code self-documenting by using descriptive names and strong naming conventions for variables, functions, and classes. In C#, for example, many developers use Pascal case when naming classes, records, structs, or public members. Another is to prefix interfaces with an I. Private, or internal, fields are prefixed with an underscore and are expressed in Camel case.
The “You Aren’t Gonna Need It” (YAGNI) principle suggests that functionality should only be included when it is absolutely needed. This doesn’t apply to things like logging, unit tests, or monitoring. Those are things you need. The problem occurs when developers add functionality because they believe it is a best practice. However, if that functionality is never used, then it contributes to confusion. Or a developer may arbitrarily split a monolithic application into several microservices, which may introduce unnecessary complexity. Those things should only be done when one has no other choice.
Use a Linter
Linters are code analyzers that check for code quality, vulnerabilities, and readability. And developers also have many free and premium options to choose from. Some IDEs may allow the developer to enforce code style rules directly in the IDE. Visual Studio, for example, enables the developer to add an “.editorconfig” that defines code style rules. Developers could use Super-Linter with Github Actions, which is a code deployment “DevOps” tool. Sonar is a premium product that provides free quality analysis for opensource projects and enterprise products for businesses. It identifies bugs, vulnerabilities, and code smells, for example, having more than a dozen lines of code in a method, which exceeds the recommended “cognitive complexity.”
Namespaces
Large complex enterprise projects often grow into hundreds of folders and thousands of files. And a well-organized namespace hierarchy reduces the amount of time to fix bugs and add features. For example, if namespaces match the folder hierarchy, it’s easier to find files.
Configure namespaces to avoid namespace conflicts. For example, if a namespace ends with a class name, it may produce an error. So, using pluralization for directories, descriptive names, or other techniques to avoid naming classes and directories the same.
A common namespace convention is:
<Company>.<Product>.<Feature>
Refactoring
Refactoring is inevitable as a project grows. Sometimes UML diagrams may be used to plan class architecture and patterns for the project. However, the developer usually doesn’t know what one has to work with until a working prototype is produced. Once that happens, it’s easier to organize the code. And that’s where refactoring comes in. And it usually involves removing unused code or comments, deduplicating code, simplifying classes or methods, or moving code into separate layers.
Code Reviews
Code reviews should be conducted regularly to ensure quality code. This could be performed by a senior developer who looks at the code and provides suggestions. This process could be skipped if no suggestions need to be made. However, junior-to-mid-level developers, by nature, often have difficulty understanding engineering concepts and have difficulty organizing their code. So, that code needs to be reviewed to ensure it doesn’t create an engineering problem or code that is difficult to maintain overtime.
Comments
Provide comments to explain the purpose and description of classes and methods. This helps to shorten development time by enabling other developers to navigate, debug, and extend the code with less confusion.
Design Principles
Often developers follow design principles to help them write and organize their code. Object oriented programmers, for example, should learn the SOLID principles. For example, the Single Responsibility Principle of the SOLID Principles states that every model, class, or function should only have a single responsibility. This keeps the code simple to understand and maintain. The Open/Closed Principle states that software should be open for extension, but closed for modification. This makes the application extendable without introducing the risk of breaking it.
Design Patterns
Design patterns help the developer to organize code and solve common problems. And depending on the language and development environment, developers may face different problems. For example, someone who works in an engineering language, such as C, C++, Rust, or GoLang, may use different patterns than someone who develops using an application development framework, such as Java or .NET. Application development frameworks are designed to make the development experience easier. For example, the developer doesn’t have to rely on patterns to refresh the user interface since many of those solutions enable the developer to bind the user interface directly to the data.
Today, many languages are trending toward adding functional programming features. And because of that, a builder pattern is a good functional programming pattern to start with. It’s particularly useful in circumstances where the developer needs to create a library to build complex data structures. The following is a simple builder pattern written in C#. This is truly is an example of over-engineering since creating an entire class to construct a name is not necessary. Patterns should be used to make the code more readable and maintainable. When patterns make the code unnecessarily complex, they are sometimes called anti-patterns or over-engineering.
var fullname = new NameBuilder()
.AddFirstName("Adam")
.AddLastName("Smith")
.Build();
Console.WriteLine(fullname);
public class NameBuilder
{
private readonly StringBuilder? _builder;
public NameBuilder()
{
_builder = new StringBuilder();
}
public NameBuilder AddFirstName(string firstName)
{
_builder!.Append(firstName);
return this;
}
public NameBuilder AddLastName(string lastName)
{
_builder!.Append($" {lastName}");
return this;
}
public string Build()
{
return _builder!.ToString();
}
}
Avoid Tight Coupling
Tight coupling is a common culprit responsible for making code unmaintainable. Reducing tight coupling means being able to swap out components without having to significantly modify the application code. For object-oriented programmers, this means following the Dependency Inversion Principle of the SOLID Principles, which states that modules should depend on abstractions instead of concrete details. This enables the developer to create libraries that may be swapped out, tested, or reused in multiple projects.
Strategies for Avoiding Tight Coupling
- Dependency Injection
- Componentization
- Modular design
Dependency Injection (DI), for object-oriented programmers, is one of the best candidates for avoiding tight coupling. DI enables the developer to move code out into application layers, or code libraries, that may consist of business logic, database access, or communication. Or it could be something as simple as a validation library that helps the developer validate data. By moving that validation library into its own layer and applying the adapter pattern, it becomes easy to replace that validation library in the future without having to modify the application code. And that saves a lot of time and effort.
DI also enables the developer to address cross-cutting concerns, or libraries that may need to be accessed in other libraries. An example would be a logger that should work in all layers without having to reference the logger, specifically, in those layers. Instead, the interface for that logger is used.
And lastly, developers need to avoid leaky abstraction in which layers are so tightly coupled that they allow the developer to call implementation logic directly.